Method for decreasing variability in a moisture analyzer

ABSTRACT

A method for analyzing moisture content in an analyzer. In one embodiment a sample is introduced into an analyzer and an initial weight is obtained. The sample is then fortified where it is allowed to pick-up moisture. The temperature of the analyzer is increased and an initial fortified point is obtained wherein the sample has returned to its initial weight. Thereafter the analyzer obtains the final moisture content of the sample at a test finish time. In one embodiment satellite analyzers are biased against a standard analyzer so that more uniform results are obtained.

CROSS REFERENCE TO RELATED APPLICATION

This application is a divisional application of co-pending U.S. patentapplication Ser. No. 12/873,907, entitled “Method for DecreasingVariability in a Moisture Analyzer,” filed Sep. 1, 2010, the technicaldisclosure of which is hereby incorporated by reference in its entirety.

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates to a method for use in an analyticalfurnace.

2. Description of Related Art

Analyzers can be used to measure or calculate a product's weight,moisture, volatiles, fixed carbon, ash, etc. of a sample. Often ananalyzer utilizes a furnace or other heat source to heat a sample. Onetype of analyzer is a thermogravimetric analyzer which periodicallyweighs the sample. The analyzer utilizes ASTM standards to analyze thesample and provide the desired reading. The sample is first initiallyweighed. Thereafter it is subjected to a controlled temperature profilewhere it is periodically weighed to determine weight loss. The moisturecontent can be calculated based on the measured weight loss.

The temperature of the sample within the analyzer is measured andcontrolled using a temperature sensor such as a thermocouple. Oftenthermocouples and other temperature measuring devices drift and becomeinaccurate over time. As the thermocouples become inaccurate, thecontrol scheme which controls the temperature of the sample oftensubjects the sample to non-uniform temperature ramp-up which affects theamount and rate of moisture loss from the sample. As such, thetemperature profile is not accurately known or controlled, which canresult in increased error and variability. Accordingly, it is desirableto have a method which accounts for and overcomes this inaccuracy.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features believed characteristic of the invention are setforth in the appended claims. The invention itself, however, as well asa preferred mode of use, further objectives and advantages thereof, willbe best understood by reference to the following detailed description ofillustrative embodiments when read in conjunction with the accompanyingdrawings, wherein:

FIG. 1 is perspective view of an analyzer in one embodiment.

FIG. 2 is a temperature and moisture profile from a plurality ofanalyzers.

FIG. 3 is a temperature and moisture profile utilizing thermalfortification.

FIG. 4 is a temperature and moisture profile from a plurality ofanalyzers.

FIG. 5 is a temperature and moisture profile from the same analyzers ofFIG. 4 but utilizing thermal fortification.

FIG. 6 illustrates the two dehydration curves from FIGS. 4 and 5.

FIG. 7 illustrates the temperature and moisture profiles utilizingthermal fortification and biasing.

DETAILED DESCRIPTION

Several embodiments of Applicant's invention will now be described withreference to the drawings. Unless otherwise noted, like elements will beidentified by identical numbers throughout all figures. The inventionillustratively disclosed herein suitably may be practiced in the absenceof any element which is not specifically disclosed herein.

FIG. 1 refers to an analyzer in one embodiment. As used herein ananalyzer refers to a device which can determine the moisture content ofa sample. The analyzer may also have additional capabilities. In oneembodiment the analyzer accurately weighs a sample as it is being heatedto determine the moisture lost over time. In one embodiment the analyzercomprises a forced air oven. Virtually any dehydration oven that canmeasure weight loss over time can be utilized. In one embodiment theanalyzer comprises a thermogravimetric analyzer. As depicted, theanalyzer comprises a plurality of apertures 101. In one embodiment theanalyzer comprises only a single aperture 101 whereas in otherembodiments the analyzer comprises more than one aperture 101. In oneembodiment the analyzer comprises ten or more apertures 101. In oneembodiment the apertures 101 are located on a plate 103, and in oneembodiment the apertures are evenly spread across the circumference ofthe plate 103. Sitting within each aperture is a crucible 102. Thecrucible 102 is used to contain the sample. The crucible 102 can be madeof any material which can tolerate elevated temperatures and which willnot react with the sample. In one embodiment the crucible 102 comprisesa ceramic material.

The sample can comprise virtually any material. In one embodiment thesample comprises food stuffs such as dough, baked product, friedproduct, or extruded product. The sample can also comprise polymers,plastics, paper, wood, coal, or any product that has its moisturecontent determined. In one embodiment the material comprises a lowmoisture product. In one embodiment the material comprises an initialmoisture content of less than about 30%. In another embodiment thematerial comprises an initial moisture content of less than about 10%.In still another embodiment the material comprises an initial moisturecontent of less than about 5%. In one embodiment the material ishydroscopic and cannot be aggressively dehydrated at high temperaturesbecause components other than water will volatize or flash off.

In one embodiment the analyzer comprises a heating element. The heatingelement can comprise any device used to supply heat, including but notlimited to, electric heat or heat through combustion. Virtually any typeof heat that can dehydrate a product can be used. The temperature withinthe analyzer is measured by at least one temperature sensor 104. Thetemperature sensor 104 can be located at virtually any location withinthe analyzer. In one embodiment the temperature sensor 104 is located ata location below the plate 103. The temperature sensor 104 can comprisea thermocouple or other suitable temperature sensor. In one embodimentthe temperature sensors 104 are coupled to a control system. Thetemperature sensor 104 provides a signal to the control system toindicate the temperature within the analyzer. The control system cancomprise any control system known to control a system or process. In oneembodiment the control system adjusts process variables to obtain adesired set point. A process variable is any variable which can beadjusted and includes temperature, humidity, pressure, etc. It should beunderstood, that as used herein “obtain” refers to obtaining or reachinga set-point within an acceptable margin of error. If the acceptablemargin of error is 20%, then if the measured moisture content is within20% of the set point moisture content then the moisture contentset-point has been obtained.

In one embodiment the temperature sensor 104 is used to obtain aset-point temperature. A set-point temperature is the temperature thatthe analyzer seeks to obtain. In one embodiment, the set-pointtemperature is obtained by comparing the measured temperature relayedfrom at least one of the temperature sensors 104 to the desiredset-point temperature. A control system then adjusts the processvariables as necessary to obtain the desired set-point temperature. Inone embodiment the control system adjusts the heating element.

The analyzer further comprises at least one balance. A “balance” as usedherein refers to any device which determines the weight of a sample. Inone embodiment the analyzer comprises a single balance and each crucible102 is sequentially rotated and weighed with the balance. In oneembodiment the crucibles 102 are first tared prior to introducing thesample into the analyzer. In one embodiment the plate 103 rotates untilthe sample desired to be weighed is above the balance. The plate 103then lowers so that the desired crucible 102 is supported by the balanceand its weight is determined. Thereafter the plate 103 raises, rotates,and weighs the next crucible 102 in line. In this manner the initialweight of each sample is obtained. In one embodiment comprising nineteencrucibles 102, each sample is weighed approximately every four minutes.In such an embodiment the weight of the sample is recorded and obtainedevery four minutes. Thus, the moisture gain or loss can be measuredagainst time. In other embodiments the number of crucibles 102, as wellas the rotation time, will be adjusted. For example, one embodimentcomprises fifteen crucibles which are weighed every three minutes.

In operation, the crucible 102 in the first position is first filledwith a sample and weighed to obtain an initial weight. Thereafter, acrucible 102 next in succession is filled and weighed. In the prior artoperation, the analyzer is then ramped to a set-point temperature. Asthe sample is heated its moisture content decreases as it losesmoisture. The set-point temperature is chosen to obtain a desired finalmoisture content. In operation, the set-point temperature utilized toyield the desired final moisture content varies wildly across differentanalyzers.

The amount of heat supplied to the samples (Q) can be defined asfollows,

Q _(heat transfer to sample) =U*Area*(T _(System Set Point) −T_(boiling))

Where

-   -   T_(System Set Point): Is the set-point temperature    -   T_(boiling): Is the boiling temperature of water    -   U*Area: Is the heat transfer co-efficient and the area

The boiling temperature will be fairly constant in a single location butcan change at different locations due to elevation changes and otherfactors such as weather conditions. The U*Area segment of the equationshould remain relatively constant between systems but may changeslightly due to system degradation, etc. However, the set-pointtemperatures often vary across systems. This can due in part tothermocouple drift as discussed previously. Even the same model ofanalyzers which operate within the same room can require variedset-point temperatures to achieve a desired moisture. In the prior artoperation, if a specific moisture is not reached then the set-pointtemperature is adjusted accordingly. The set-point temperature can driftfor a variety of reasons including thermocouple drift whereby thethermocouple gradually becomes less accurate. Such drift can cause theset-point temperature to vary from the actual operating temperaturecausing inconsistencies.

In one embodiment, Applicant has discovered that to make the amount ofheat supplied to a sample uniform across various analyzers thedehydration driving force, which is the difference between thetemperature within the analyzer and the boiling point temperature,should be held constant. As discussed above the U*Area portion of theequation is relatively constant across analyzers of the same type. Thus,by making the dehydration driving force uniform, the test can becomemore accurate. As will be discussed below, the set-point temperature foreach analyzer will be adjusted to ensure the dehydration driving forceremains approximately constant.

FIG. 2 illustrates the temperature and moisture content profiles of anumber of analyzers in different locations across the country. Eachprofile represents a reference product performed on 39 differentanalyzers located at various places in the United States. All of thereference product was prepared at the same time, at the same location,and were packed into centrifuge tubes to prevent moisture pickup priorto analyzing each sample at the different analyzers. The analyzersutilized were a TGA 701 thermogravimetric analyzer made by LecoCorporation of St. Joseph Michigan. Each analyzer analyzed two referencesamples in a single batch. As depicted, the reference product comprisedpotato dough.

As noted, the analyzers are analyzing reference samples which have anapproximately equal starting moisture content. The left axis shows theweight of the sample that has been lost or gained over time expressed inpercent moisture. A positive moisture reading indicates that moisturehas been lost whereas a negative reading indicates that moisture hasbeen gained. It can be seen that the final moisture reading ranges fromabout 1.5% to about 1.2%. Accordingly, this resulted in a range ofapproximately 0.3% moisture. This means that the same sample yieldedvarious results on different analyzers. Because the moisture readingobtained from the analyzer is often used to control processingconditions for making a final product, the variance across analyzers canresult in significant product variability. Reducing the variance of themoisture content obtained by the analyzer will result in decreasedproduct variability. Further, as will be discussed in detail below, themoisture content has an affect on many final product attributesincluding staleness, number of defects, level of scorching, acrylamideformation, product hardness, etc. These and other attributes can bebetter controlled by better controlling the moisture content.

FIG. 2 also illustrates the temperature profile of the sample. As can beseen, each analyzer seeks to obtain the set-point temperature. As thetemperature profile becomes horizontal, the temperature set-point hasbeen obtained. As can be seen, the temperature set-point varies fromabout 109° C. to about 97° C. across different analyzers. Thisillustrates the inaccuracy of the temperature sensors. As an example,one of the analyzers has a set point temperature of about 97° C. whichis less than the boiling temperature of water. Because water is beingevaporated from the sample, it is clear that the analyzer is operatingabove 100° C. Accordingly, the temperature reported by the sensor isincorrect. As discussed, each of these varying set-point temperatures ischosen to achieve a set-point moisture content. In the case of theanalyzer with a set-point temperature of 97° C. it is possible that thistemperature sensor trended downward so that a progressively lower andlower set-point temperature was required to achieve the desired moisturecontent. The actual set-point temperature may be 105° C. but is beingread as 97° C.

FIG. 2 also illustrates the temperature profile before the set-pointtemperature is obtained. It can be seen that some of the analyzersovershoot the set-point temperature. This can be due in part todifferent control systems used to control the temperature as well aserrors in the temperature sensor. Thus the sample is being subjected totemperatures which can be much greater than the set-point temperature.Because water vapor is a function of temperature, the ramp profile hasan affect on the water vapor of the sample. This affects the measuredmoisture content. As can be seen from the figure, the analyzers havedifferent ramp profiles. A ramp profile is the temperature profile whilethe set-point temperature is being obtained.

Aside from the differences already discussed, it can be seen that thetotal testing time differs from each test as well. The total testingtime refers to the total length in time from when the sample is firstloaded until the test is complete. In one embodiment the test iscomplete when the rate of change in the moisture content reached aspecified value. It can be seen that there is great variability in thetotal testing time which is undesirable as it increases variability ofthe product and product control.

The previous methods of measuring moisture content are inadequate for avariety of reasons. First, it often takes time to load all the samples.During this waiting time, the moisture content of the sample is likelyto change due to the sample taking in or losing moisture to the air. Asthose skilled in the art will understand, the change in moisture contentwill depend on a plurality of factors including sample moisture content,temperature of the sample, temperature of the air, humidity of the air,etc. Further, the material may have components which can either oxidizeor volatilize which also changes the weight of the sample, which in turnchanges the moisture content. As can be appreciated, the first loadedsample may change more than the last loaded sample as the first loadedsample is often exposed to air for a greater period of time than thelast loaded sample. This introduces non-uniformity into the system.

Second, as discussed, the ramp profile is not uniform across the variousanalyzers. Because water vapor is a function of temperature, the slopeof the ramp profile affects the water vapor of the sample. This altersthe amount and speed of moisture loss which introduces furthernon-uniformity into the system.

Third, as discussed, the total testing time is not uniform across thevarious analyzers. This results in some samples being analyzed for amuch longer time than other samples which can introduce non-uniformityinto the system. Applicants have discovered several methods, discussedherein, which can overcome and eliminate the non-uniformity of the rampprofiles and the total testing times. Further, as discussed above, oftenthe first loaded samples have increased exposure to air compared tolater loaded samples. Applicants can overcome this and other moisturevariances in the samples caused by exposure to air by the methodsdiscussed herein. Finally, by employing the methods discussed herein,Applicants eliminate the non-uniformity by overcoming or accounting forthe issues previously addressed such as incorrect temperature sensorsresulting in set point temperature variances.

In one embodiment the samples are thermally fortified during the ramp-upprofile. In one embodiment, the thermal fortification comprises allowingthe sample to pick-up moisture before heat is applied to removemoisture. Picking-up moisture refers to increasing the moisture contentof the sample. This can be accomplished by opening the lid of theanalyzer so that the samples are subject to the air, for example. Theair can be modified such as by using a humidifier to obtain a desiredhumidity. Those skilled in the art will understand that the humidity ofthe air can be adjusted to control the rate of moisture taken-up orgiven-up by the sample. In one embodiment the air used during thethermal fortification ranges from about 0 to about 100% relativehumidity. In another embodiment the air ranges from about 50 to about90% relative humidity. In another embodiment the air ranges from about60 to about 85% relative humidity. In one embodiment the air is about95% non-condensating. Greater than about 80% relative humidity resultsin aggressive moisture take-up. Different relative humidities will beappropriate for different types of product. As discussed, the humidityof the laboratory air can be controlled. In another embodiment thehumidity of the analyzer is controlled. In such an embodiment humid aircan be pumped to, or circulated through the closed analyzer to maintaina desired humidity. Likewise, the temperature of the air in thelaboratory or within the analyzer can be controlled to adjust the rateof moisture taken-up by the sample.

In one embodiment the samples are loaded as previously described. Eachsample is weighed to obtain an initial weight. Thereafter the sample isallowed to sit for a time to pick-up moisture until a specified moisturecontent has been reached. This is referred to as thermal fortification.The amount of time required to reach the desired moisture content willdepend on a plurality of factors as discussed above. As will bediscussed below, in one embodiment thermal fortification decreases thenon-uniformity of the ramp profile and accounts for the inconsistenciesof loading samples.

In one embodiment it is desirable that the sample increase its moisturecontent by about 1%. Those skilled in the art will understand thathigher or lower increases may be suitable for different products. Forexample, some products may require moisture content increases of lessthan 1%, for example, about 0.3%, before thermal fortification has beenachieved. In some embodiments, increasing the moisture content by morethan about 10% can change how the product releases the moisture, whichmay be a negative consequence. This change can have an undesirableimpact on the moisture reading. In one embodiment comprising a pluralityof samples, the samples are allowed to pick-up moisture until eachsample has been increased by at least 1%.

FIG. 3 shows a temperature and moisture profile for an analyzer usingthermal fortification. The reference sample employed was a potato chipdough, and the sample was analyzed on a TGA 701. As depicted, thesamples initially had a moisture reading of zero, meaning there had beenno change in moisture content. They were allowed to sit for a time untilthe desired moisture is obtained. As depicted the set-point moisturereading is about 1.0%.

FIG. 3 also depicts the temperature profile of the analyzer. As depictedthe ramp profile does not begin until the samples have obtained thedesired moisture content. Put differently, the analyzer does not applyheat to obtain the set-point temperature until after a set-pointmoisture content has been obtained. It can be seen that once the sampleobtains the moisture set-point, then the temperature of the analyzerincreases. As the temperature increases, the sample begins to losemoisture. Thus, the moisture curve which previously had a negative slopenow has a positive slope. At some point, the moisture curve passes thex-axis and a moisture reading of zero is obtained. At this point, thesample has returned to its initial weight before the fortifying. Thismeans that the sample has lost the amount of moisture it had previouslygained. This point is referred to as the fortified initial point.

The fortified initial point can be a data point or it can be calculated.As previously stated, in one embodiment samples are analyzed atscheduled intervals. As discussed, in one embodiment a given sample isanalyzed every four minutes. Accordingly, in some embodiments a firstdata point will fall below the x-axis indicating a moisture gain while asecond data point will fall above the x-axis indicating a moisture loss.This means that the fortified initial point occurred at some pointbetween the first and second data point. Methods known in the art suchas interpolation, regression, etc. can be used to determine the point inthe time where the moisture reading is about zero. In such an embodimentthe fortified initial point is calculated. The calculation can takeplace manually or can be calculated with software.

Referring to the temperature profile, as depicted, the temperatureprofile has been ramped by the time of the fortified initial point isreached. Put differently, the set-point temperature has been obtainedprior to reaching the fortified initial point. This results in severalbenefits. As previously described, the temperature, the temperatureprofile, and the slope of the ramp-up have an affect on moisture.Because the set-point temperature is obtained, or obtained within anacceptable tolerance, before the fortified point is reached, thedeviations due to non-uniform ramp profiles, temperature profiles,slopes, etc. is minimized or eliminated. As previously discussed thesedifferences can be due in part to differences in controllers, processcontrol equipment, temperature sensors, etc. across the variousanalyzers. The thermal fortification removes these variabilities andallows each sample to be treated in a uniform manner. Thus, in oneembodiment by the time sample has again reached its initial weight atthe initial fortified point the set-point temperature will have beenobtained. Accordingly, each sample will be subject to the sametemperature. As a result, each sample will have approximately the sameheat supplied to the system as determined by the equation listed above.

As previously discussed, in some embodiments the analyzers will comprisea plurality of samples. In some embodiments only one sample can beweighed at a given time. As such, in one embodiment the first sampleloaded will begin to take-up moisture while the other samples are beingloaded. In such embodiments it is possible that the first sample willreach the moisture set-point faster than the later loaded samples. Inone embodiment it is desirable to ensure that each sample reach themoisture set-point even if this means that the first sample may exceedthe moisture set-point. This may also mean that each sample may have itsown fortified initial point. Because the first sample may have exceededthe moisture set-point its fortified initial point may occur later intime compared to the later loaded samples. This is acceptable and onlyaffects the time of test for that sample, which is discussed below.

In one embodiment the samples are analyzed until the final moistureset-point is obtained. In one embodiment the final moisture readingset-point is about 1.3. This means that the weight of the sample isdecreased by about 1.3%. The point in time that the final moistureset-point is reached is referred to as the test finish point. Asdiscussed with the fortified initial point, an analyzed data point maynot fall on the test finish point. Specifically, a first data point mayfall below the final moisture set-point and the second data point mayfall above the final moisture set-point meaning the test finish point islocated between the first and second data points. In such embodimentsmethods previously discussed can be used to calculated the test finishpoint. At the test finish time the final weight of the sample, and thusthe moisture content of the sample is obtained or calculated.

The difference in time between the test finish point and the fortifiedinitial point is referred to as the time of test. In one embodiment thetime of test ranges from about 10 minutes to about 3 hours. In oneembodiment the time of test is about 2 hours. As previously discussed,the amount of time from when the sample was first loaded into theanalyzer until the test finish point is referred to as the total testingtime. In one embodiment the total testing time ranges from about 20minutes to about 9 hours. In one embodiment the total testing time isless than about 4 hours. The fortification method described above willincrease uniformity and decrease variance.

In one embodiment, two or more samples are analyzed and the data iscollected. In one embodiment as much as 10 or more samples are analyzedand the data collected. From this data an average curve can be createdand the average time of test can be obtained. In one embodiment the timeof test is the average time of test obtained from a plurality ofsamples. The obtained time of test can then be used in subsequent testsof that product to determine when the final moisture content isobtained. Specifically, the analyzer when analyzing that product willrun for the time of test and the moisture reading at the end of the timeof test will be utilized. In such an embodiment the test finish timeoccurs at a specified time after the initial fortified point. Thereaftera uniform test of time can be used in multiple runs. This results in amore uniform time of test which results in more uniform results. Whenthe analyzer is referred to as running this means the analyzer iscollecting data.

FIG. 4 is a temperature and moisture profile from a plurality ofanalyzers. The analyzers employed were TGA 701. Thermal fortificationwas not employed in the samples depicted in FIG. 4. As can be seen,compared to FIG. 1, FIG. 4 illustrates less variability in the rampprofile and moisture spread. This is due in part because all of theanalyzers were located in a single location, thus, the boilingtemperature remained constant across all analyzers. The analyzers werebiased from a forced air oven reading. If the results from one of theanalyzers deviated from the forced air oven reading by greater than0.15% moisture the set-point temperature was adjusted 2° C. for each0.5% deviation. This figure illustrates the variability in the rampprofile and the dehydration curves. This figure illustrates the totalvariability without using thermal fortification and without biasing eachanalyzer against a standard, which is discussed in detail below.

FIG. 5 is a temperature and moisture profile from the same analyzers ofFIG. 4 but utilizing thermal fortification. The analyzers used in FIG. 5were not biased but instead set to the same set-point temperature of110° C. As can be seen the dehydration profiles in FIG. 5 still deviatedslightly. This is due to the error of measuring the absolute temperatureof the analyzer.

In FIG. 5 the samples were allowed to pick-up moisture for a specifiedamount of time. As can be seen, some samples were allowed to pick-upmoisture for about 6500 seconds while other samples were allowed topick-up moisture for about 4500 seconds. In the embodiment depicted,increasing the pick-up time had a minimal effect on the samples'profile. This is due in part to the set point temperature being achievedbefore the initial fortified point.

FIG. 6 illustrates the two dehydration curves from FIGS. 4 and 5 on thesame time axis. Put differently, the temperature and dehydrationprofiles of FIG. 5 have been time shifted so that the time zero is theapproximate initial fortified point. As can be seen, the fortifiedsamples (from FIG. 5) end at the same time. Put differently, they have auniform test of time. Conversely, the un-fortified samples (from FIG. 4)end at dissimilar times.

As the curves begin it can be seen that the un-fortified samples achieveinstant separation. This is shown in box 603. This is due in partbecause of dissimilar ramp profiles. After a short time the curves ofthe un-fortified groups become tighter due to different driving forcesset by the temperature biasing. This is shown in box 604. Thereafter,the un-fortified samples again begin to diverge because of the largedifferences in dehydration driving force (difference in set-pointtemperature and boiling temperature) due to the compensation for theramp profile variability. Put differently, because the ramp profileswere non-uniform the dehydration profiles diverge accordingly. This isillustrated in box 605. The fortified samples also have initialseparation as shown in box 601. This is due to a difference indehydration driving force due to error in the temperature measurement.Conversely, the curve separation for the fortified data samples remainssimilar as shown in box 602 because the dehydration driving forceremains constant.

As can be seen, the dehydration curves of the fortified samples do notcross one another because the ramp profile variability has beendampened. As such the curves do not have to compensate for the rampprofile variability. More specifically, previously the systems werebiased to accommodate the variability in ramp between systems. A highenergy input during ramp for one system would likely mean a lower setpoint temperature to compensate for high moisture readings. Conversely,a low energy input ramping system would have a higher temperature setpoint to compensate for low moisture readings. Because ramp variabilityhas been removed, the curves for the fortified samples do not cross oneanother. Conversely the dehydration curves of the un-fortified samplesdo cross one another. This is due in part to the differences indehydration driving force used to compensate for ramp profilevariability.

The method described can be used on a single analyzer or may beimplemented in all analyzers for a given system. In some embodiments asystem may comprise a plurality of analyzers. As an example, a systemmay comprise three dissimilar analyzers across the nation or across theworld. As previously discussed, even if the analyzer is of the samebrand with the same model, the results can vary greatly. As shown inFIG. 1, different analyzers yielded products which had a moisturereading difference of about 0.3%. As stated previously, this can resultin an inconsistent product and inconsistent process control. As such, inone embodiment it is desirable to conform each analyzer so that theresults are more uniform.

In one embodiment one analyzer is selected to be the “standardanalyzer.” The “standard analyzer” refers to the analyzer to which thesatellite analyzers will be conformed and/or measured. The satelliteanalyzes refers to any analyzer in a system other than the standardanalyzer. A satellite analyzer can be located across the country, in adifferent part of the world, or on the same shelf as the standardanalyzer. In one embodiment each analyzer comprises a process variablewhich can be controlled. In one embodiment the process variable can beadjusted to obtain a desired set-point.

In one embodiment to conform the satellite analyzers to the standardanalyzer the standard analyzer first analyzes a reference product set. Areference product set refers to an amount of similar product. In oneembodiment a product set refers to product which is ground andhomogenized to make the product as identical as possible. In oneembodiment the reference product set comprises a sufficient amount ofproduct to supply a plurality of analyzers. In one embodiment theproduct set is ground, placed inside a plastic sealable container suchas a centrifuge tube. In one embodiment the container or set ofcontainers is placed into a high barrier film bag. The bag is nitrogenflushed and sealed to prevent moisture pick-up or release.

In one embodiment the seal comprises a material which acts as a moisturebarrier. In one embodiment the sample is placed in a desiccatingenvironment. Thus, in one embodiment the product set or sample isprepared by placing the sample in a container and sealing the container.Such a method will adequately maintain the approximate moisture contentof each sample in the product set. Thereafter, at least one sample fromthe product set is loaded into the standard analyzer. The standardanalyzer performs as previously described, and the sample is analyzed.The resulting curve is referred to as a standard analyzer profile. Inone embodiment the standard analyzer profile comprises a temperature anddehydration profile. In one embodiment the analyzer utilizes the thermalfortification step previously described. Thereafter, at least one samplefrom the product set is then inserted into the satellite analyzer andthe same method is performed. The resulting curve is referred to as thesatellite analyzer profile and can include the same profiles as thestandard analyzer profile. Thereafter the resulting curves from thestandard analyzer and at least one satellite analyzer are compared. Inone embodiment the resulting data is inserted into a computer programwhich biases the operation of the at least one satellite analyzer tomatch the profile produced by the standard analyzer. There are a varietyof objective criteria which can be used to determine if the satelliteanalyzer sufficiently matches the profile produced by the standardanalyzer. Those skilled in the art will understand that whether asatellite analyzer matches the standard analyzer will depend upon theacceptable margin of error. This can be quantified by using acoefficient of determination (R²) or other statistical measurements. Inone embodiment the average of four reference samples measured over twobatches is compared to the standard analyzer, and if the difference inmeasured moisture content is less than about 1.0% then the satelliteanalyzer is considered to match the standard analyzer. In otherembodiments the difference must be as low as 0.1%. In still otherembodiments the difference must be less than about 0.05%. In oneembodiment the biasing process is an iterative process.

In one embodiment the algorithm which biases at least one satelliteanalyzer utilizes Projections on Latent Structures (PLS) on dehydrationcurves and temperature set points to map out a latent space. In oneembodiment the dehydration profile is an input and is used to determinethe temperature offset for dehydration driving force relative to anothersystem. By inputting the satellite system temperature set point, thebiasing algorithm can report what temperature to set that system to sothat if it were to run a reference sample, the resulting curve wouldbest match a curve generated by a reference sample on the standardsystem. In one embodiment the standard system performs the biasing.

In one embodiment the underlying assumption is that while the absolutetemperature of the analyzer is not being accurately measured by thetemperature sensor, it is assumed that the relative temperature changescan be monitored accurately by the various temperature sensors. Putdifferently, it is assumed that while the actual absolute temperature ofthe analyzer is not measured correctly by the temperature sensor, thesensors are capable of detecting relative temperature change. As anexample, if the temperature sensor provides a temperature reading of105° C. but it is actually operating at 110° C., as measured by aseparate temperature sensor, it is assumed that if the analyzer isadjusted to operate at 115° C. the temperature sensor will have areading of 110° C. As previously discussed, the temperature differencebetween the set-point temperature and the boiling temperature is thedriving force behind the heat transfer in the analyzer. As such, even ifthe actual set-point temperature is not known, so long as the relativetemperature can be known and controlled, then the analyzer can bebiased. Again even if the absolute operating temperature is unknown solong as the operating temperature can be adjusted and controlled thenthe analyzer can be biased. In this regard, the set point temperaturevariance issue is minimized as the set point is controlled even if thetemperature sensor is reporting an incorrect operating temperature.Accordingly, at least one satellite analyzer is biased to duplicate thestandard analyzer.

Such biasing and system operation allows direct comparison of resultsbetween analyzers, that under standard operating methods, would generatea significant systematic bias. Those skilled in the art will understandthe multitude of benefits that flow from this direct comparison whichinclude the ability to better control product attributes, bettercomparison of products from different plants, etc. As discussed, in oneembodiment all analyzers will be controlling to the same moisturecontent at all sites that have been properly biased with this method.The result will significantly shrink the range of moisture contentproduced in all systems. As those skilled in the art will understand,moisture content is an important product attribute that must becontrolled in consumer packed goods. Thus, this method allows for bettercontrol over moisture content which has many benefits.

In one embodiment after a satellite analyzer has been biased it can beused to create a gold standard curve and moisture reading for a specificproduct. The standard analyzer can also be used to create a goldstandard. In one embodiment, a statistically significant number ofsamples are analyzed and the curves generated are averaged to create agold standard. The gold standard shows the expected dehydration profilefor reference product. When all other systems are biased to the standardanalyzer, they should produce this curve on average when making thecorrect product.

In one embodiment wherein the satellite analyzer is located in a plant,the gold standard is created from hot product gathered at the plant. Thestandard system may be centrally located at a headquarters or lab whereobtaining hot product is not possible. In one embodiment, the productsamples used to create the gold standard is certified under standardprotocol and hot samples from the production line are obtained andanalyzed on the newly biased plant system. In one embodiment productproduced, harvested, collected, or otherwise obtained is inserted intothe analyzer and analyzed. In one embodiment product obtained from amanufacturing line is inserted into the analyzer.

In one embodiment the gold standard further dictates time of testrequired to reach the desired moisture reading if the system is beingretrofitted to report a certain moisture specification. For example, ifthe gold standard notes that the time of test is 2 hours then subsequentsamples are analyzed with a set-point temperature determined by the PLSbiasing algorithm and run for a time of test of 2 hours beyond the pointwhere the sample returns to its original weight after being allowed togain moisture from the environment. In such an embodiment rather thanoperating until a moisture content is achieved the tests are run with atime of test of 2 hours. Thus, all tests utilizing that specific goldstandard are uniform in length. In other embodiments, an arbitrary timeof test may be chosen and the resulting moisture reading is thedetermined specification for that product. It should be noted that insome embodiments the elevation and system degradation of the satellitesystems may result in a different test of time than that predicted bythe gold standard.

FIG. 7 illustrates the temperature and dehydration profile of a biasedsystem. The model demonstrated in FIG. 7 was created by collecting dataand curves from the standard analyzer across a variety of temperatures.The model was then used to predict temperature set points for thesatellite analyzers.

The curves labeled “STANDARD” represent the standard analyzer profilesrun with a set-point temperature of 110° C. The curves labeled“STANDARD” are the curves that the model is trying to replicate on theother satellite analyzers. The curves labeled 115 represent a satelliteanalyzer analyzing product from the same product set run with aset-point temperature of 115° C. The curves labeled 100 represent thesame satellite analyzer as the curves labeled 115 analyzing product fromthe same product set but run with a set-point temperature of 100° C. Theresulting curves labeled 115 were inputted into the model to obtain apredicted set-point for the satellite analyzer that would result in thesatellite analyzer matching the standard analyzer. Using the curveslabeled 115, and their initial set point of 115° C., the model yielded aset-point temperature of 110.1. Using the curves labeled 100, and theirinitial set point of 100° C., the model yielded a set-point temperatureof 109.4° C. Thus, using different curves, the model predicted asubstantially similar set-point temperature for the analyzer. Thesamples were analyzed on a TGA 701 as previously discussed. This modeldid not allow for adjustments of a fraction of a degree. Putdifferently, the set-point temperature can only be set to the nearestdegree. Consequently, a validation trial was conducted at both 109° C.,as predicted from the curves labeled 100, and at 110° C., as predictedfrom the curves labeled 115. The curves labeled 109 illustrate thesatellite analyzer run with a set point of 109° C. whereas the curveslabeled 110 illustrate the satellite analyzer run with a set point of110° C.

The average final moisture content from the curves labeled “standard”was 1.68%. The average final moisture content from the curves labeled100 was 1.51%, and the average final moisture content of the curveslabeled 115 was 1.80%. After using the model, the average final moisturecontent of the curves labeled 109 was 1.70% whereas the average finalmoisture content of the curves labeled 110 was 1.74%. However, the finalmoisture content of the curves labeled 110 was calculated using anoutlier which skewed the results. Those skilled in the art willunderstand that the effect of such outliers can be handled viastatistical means. Further, those skilled in the art will understandthat increasing the number of trials to obtain a more accurate mean willresult in a more accurate model.

As those skilled in the art will understand, the analyzers can be usedfor a variety of purposes. In one embodiment the analyzers are used tocalibrate process sensors. A process sensor includes any sensor thatmeasures and/or controls any process variable on a process. Asdiscussed, a process variable refers to any process condition which canbe measured or controlled and includes, but is not limited to, moisturecontent, temperature, pressure, frying time, etc. A process variablealso includes product attributes previously discussed includingstaleness, acrylamide concentration, etc. As discussed, productattributes are often controlled by controlling process variables.

In one embodiment the process sensors comprises an on-line sensor. Inone embodiment the on-line sensors are used to control the operation ofthe process. However, periodically samples are tested with an analyzerto calibrate the on-line sensors. The method discussed herein allows theanalyzer to become more precise, accurate and more uniform across allanalyzers in a system. This accuracy and uniformity is then passed toother processing equipment, such as the on-line sensors, throughcalibration and the like. In such embodiments, the data from theanalyzer is transmitted to the process sensor. The data can betransmitted via hardwire, wireless, or other method known in the art. Itshould be understood that the data can be transmitted directly to theprocess sensor, or it can be transmitted to a controller which controlsor monitors the process sensor. In one embodiment, the process sensormeasures at least one process variable. The measured process variablefrom the process sensor is then compared to the data received from theanalyzer, and the process sensor is calibrated using the data received.

In another embodiment, the data collected from the analyzer is sent tocontroller, whereby the controller utilizes the data to determine ifprocess variables should be adjusted. As an example, the controller maydetermine that the on-line process sensor needs calibrated. It may alsodetermine, for example, that frying time needs to be increased.

As previously discussed, moisture content has an affect on many productattributes including staleness, number of defects, level of scorching,acrylamide formation, product hardness, etc. As discussed, these andother attributes can be better controlled by better controlling themoisture content. One such example is acrylamide. Those skilled in theart understand that acrylamide increases exponentially as the moisturecontent is reduced. Thus, if the moisture content is increased, thelevel of acrylamide can be significantly reduced. In one embodimentinvolving fried potato chips, it has been determined that increasing theaverage moisture content from 1.1 to 1.3 resulted in a 25% reduction inacrylamide formation.

In an embodiment involving fried potato chips, a variance of about 0.4%moisture content resulted in about 100-150 ppb additional acrylamide insome lower moisture product. Put differently, a 0.4% variance resultedin some product having less moisture which resulted in additionalacrylamide. As noted in FIG. 1, a 0.4% variance in moisture content hadpreviously been common as the analyzers often had undesirablevariability for the reasons discussed herein. Further, because the levelof acrylamide increases exponentially as the moisture content isdecreased, a product which has 0.4% less moisture content than desirablehas more acrylamide compared to the product with the desired moisturecontent. As such, decreasing this variance allows a significantreduction in acrylamide formation.

In embodiments wherein the variance of moisture content is reduced toabout 0.05% then the amount of additional acrylamide is from about 0 toabout 25 ppb. In embodiments wherein the mean acrylamide concentrationis about 300 ppb this method resulted in a 30% increase with the 0.4%moisture content variance to a reduction of less than a 10% increasewith the 0.05% moisture content variance in moisture content. As will beunderstood by those skilled in the art, methods can be applied whichwill further decrease the variance below 0.05%. For example, a widerselection of samples will yield a more accurate mean, which in turn willdevelop a more accurate model. Further, larger samples allow forstatistical methods which can locate and eliminate undesirable outlierswhich can also result in a more accurate model. Those skilled in the artwill understand the tools and methods to obtain a more accurate model.

As discussed above, the data obtained from the analyzer can be fed tothe manufacturing line which can adjust the process control based on theobtained data. Accordingly, having decreased variance in the moisturecontent translates to decreased variance in the process control. Asdescribed above, decreasing the variance in the analyzer allows tighterand more consistent control over the process control, which can then beused to control, and reduce, the formation of acrylamide, as an example.

While the invention has been particularly shown and described withreference to a preferred embodiment, it will be understood by thoseskilled in the art that various changes in form and detail may be madetherein without departing from the spirit and scope of the invention.

Additional Description

The following clauses are offered as further description of thedisclosed invention.

-   1. A method for analyzing moisture content in an analyzer, said    analyzer comprising:    -   at least one balance;    -   said method comprising:    -   a) introducing at least one sample into said analyzer;    -   b) obtaining an initial weight of said at least one sample with        said balance;    -   c) fortifying said at least one sample to obtain a desired        moisture content;    -   d) increasing the temperature of said analyzer;    -   e) obtaining an initial fortified point, wherein said at least        one sample has returned to said initial weight at said initial        fortified point;    -   f) obtaining the moisture content of said at least one sample at        a test finish time.-   2. The method according to any preceding clause, wherein said    fortifying step comprises allowing said at least one sample to    pick-up moisture.-   3. The method according to clause 2 wherein said desired moisture    reading comprises increasing the moisture content of said at least    one sample by 1%.-   4. The method according to any preceding clause, wherein said    introducing comprises introducing at least two samples.-   5. The method according to any preceding clause, wherein said    introducing comprises introducing into a thermogravimetric analyzer.-   6. The method according to any preceding clause, wherein said    increasing of step d) comprises increasing to a set-point    temperature.-   7. The method according to clause 6, wherein said set-point    temperature is obtained prior to said obtaining of step c).-   8. The method according to any preceding clause, wherein said    increasing of step d) takes place after said at least one sample has    reached said desired moisture reading in step c).-   9. The method according to any preceding clause, wherein said test    finish time is a point in time wherein said at least one sample    reaches a desired moisture reading.-   10. The method according to any preceding clause, wherein said test    finish time occurs at a specified time after said initial fortified    point.-   11. The method according to clause 10, wherein said specified time    after said initial fortified point is uniform across multiple runs.-   12. The method according to clause 10, wherein said specified time    after said initial fortified point comprises a test of time.-   13. The method according to clause 12, wherein said test of time is    the difference in time between said initial fortified point and said    finish time.-   14. The method according to clause 13, wherein said test of time    comprises an average of a plurality of test of times observed from    at least two samples.-   15. The method according to clause 10, further comprising:    -   g) repeat steps a-f, wherein said specified time after said        initial fortified point is about the same in step f) and step        g).-   16. The method according to any preceding clause, wherein said    obtaining of step e) comprises calculating an initial fortified    point.-   17. The method according to clause 16, wherein said calculating    comprises interpolating between data points.-   18. The method according to any preceding clause, wherein said    obtaining of step f) comprises calculating the moisture content.-   19. The method according to clause 18, wherein said calculating    comprises extrapolating between data points.-   20. The method according to any preceding clause, wherein said    obtaining of step b) comprises weighing said at least one sample    with said balance.-   21. The method according to any preceding clause, wherein said    fortifying of step c) comprises fortifying in a humidity controlled    environment.-   22. The method according to any preceding clause, further    comprising:    -   g) transmitting said moisture content to a process sensor.-   23. The method according to clause 22, further comprising:    -   h) analyzing at least one process variable with said process        sensor.-   24. The method according to clause 23, further comprising:    -   i) calibrating said process sensor.-   25. The method according to clause 22, further comprising:    -   i) adjusting at least one process variable.-   26. A method for biasing an analyzer in system, said system    comprising:    -   at least two analyzers, wherein said at least two analyzers        comprises a standard analyzer and a first satellite analyzer,        and wherein each analyzer comprises at least one process        variable;    -   said method comprising:    -   a) obtaining a product set comprising a plurality of samples,        wherein said plurality of samples comprises a first sample and a        second sample;    -   b) analyzing said first sample in said standard analyzer to        obtain a standard analyzer profile;    -   c) analyzing said second sample in said first satellite analyzer        to obtain a first satellite analyzer profile;    -   d) comparing said standard analyzer profile with said first        satellite analyzer profile;    -   e) biasing said first satellite analyzer to said standard        analyzer.-   27. The method according to clause 26, wherein said biasing    comprises utilizing projections on latent structures on set-point    temperature and dehydration curves.-   28. The method according to clause 27, wherein said set-point    temperature is an input and dehydration profile is an output.-   29. The method according to clauses 26-28, further comprising:    -   f) analyzing a plurality of samples on said first satellite        analyzer to obtain a gold standard curve.-   30. The method according to clause 29, further comprising:    -   g) obtaining a test of time from said gold standard curve.-   31. The method according to clause 30, further comprising:    -   h) analyzing at least one sample by running said first satellite        analyzer for a test of time.-   32. The method according to clauses 26-31, wherein said analyzing of    step b) comprises thermal fortification.-   33. The method according to clauses 26-32, wherein said standard    analyzer profile comprises a dehydration profile.-   34. The method according to clauses 26-33, wherein said standard    analyzer profile comprises a temperature profile.-   35. The method according to clause 27, wherein said standard    analyzer is a thermogravimetric analyzer.-   36. The method according to clauses 26-35, wherein said analyzing of    step b) comprises obtaining a moisture content.-   37. The method according to clauses 26-36, wherein said obtaining of    step a) comprises sealing said plurality of samples.-   38. The method according to clauses 26-37, wherein said obtaining of    step a) comprises nitrogen flushing and sealing said plurality of    samples.-   39. The method according to clauses 26-38, wherein said biasing of    step e) results in decreased moisture content variances.-   40. The method according to clauses 26-39, wherein said biasing of    step e) results in decreasing the level of acrylamide formation.-   41. The method according to clauses 26-40, wherein said biasing step    comprises biasing said first analyzer to yield a moisture content    within 0.05% of a moisture content yielded by said standard    analyzer.

What is claimed is:
 1. A method for biasing an analyzer in system, saidsystem comprising: at least two analyzers, wherein said at least twoanalyzers comprises a standard analyzer and a first satellite analyzer,and wherein each analyzer comprises at least one process variable; saidmethod comprising: a) obtaining a product set comprising a plurality ofsamples, wherein said plurality of samples comprises a first sample anda second sample; b) analyzing said first sample in said standardanalyzer to obtain a standard analyzer profile; c) analyzing said secondsample in said first satellite analyzer to obtain a first satelliteanalyzer profile; d) comparing said standard analyzer profile with saidfirst satellite analyzer profile; e) biasing said first satelliteanalyzer to said standard analyzer.
 2. The method of claim 1 whereinsaid biasing comprises utilizing projections on latent structures onset-point temperature and dehydration curves.
 3. The method of claim 2wherein said set-point temperature is an input and dehydration profileis an output.
 4. The method of claim 1 further comprising: f) analyzinga plurality of samples on said first satellite analyzer to obtain a goldstandard curve.
 5. The method of claim 4 further comprising: g)obtaining a test of time from said gold standard curve.
 6. The method ofclaim 5 further comprising: h) analyzing at least one sample by runningsaid first satellite analyzer for a test of time.
 7. The method of claim1 wherein said analyzing of step b) comprises thermal fortification. 8.The method of claim 1 wherein said standard analyzer profile comprises adehydration profile.
 9. The method of claim 1 wherein said standardanalyzer profile comprises a temperature profile.
 10. The method ofclaim 2 wherein said standard analyzer is a thermogravimetric analyzer.11. The method of claim 1 wherein said analyzing of step b) comprisesobtaining a moisture content.
 12. The method of claim 1 wherein saidobtaining of step a) comprises sealing said plurality of samples. 13.The method of claim 1 wherein said obtaining of step a) comprisesnitrogen flushing and sealing said plurality of samples.
 14. The methodof claim 1 wherein said biasing of step e) results in decreased moisturecontent variances.
 15. The method of claim 1 wherein said biasing ofstep e) results in decreasing the level of acrylamide formation.
 16. Themethod of claim 1 wherein said biasing step comprises biasing said firstanalyzer to yield a moisture content within 0.05% of a moisture contentyielded by said standard analyzer.